Research On The Inventory And Integrated Optimization Problem Based On Nondeterministic Environment

Inventory and transportation are two sutra problems in operational research, investigation on them respectively is already considerable ripe, but the study on the integrated inventory-transportation problem is quite limited. Moreover, Inventory and transportation are two important factors that take up the biggest share of logistics cost in distribution tache of supply chain. Therefore, it is indispensable to study how to reduce total cost of inventory and transportation. On the integrated optimization problem, because it needs to integrate inventory cost and transportation cost into the same objective function, the constraints will be more complex and difficult to describe accurately the system, which determines the complexity of the problem, consequently, exploring an excellent algorithm to the problem has become the major difficulties and research hot spots. Looking into the status quo of research and application from abroad, the system, which is integrated inventory and transportation into optimization problem, is more useful to improve the efficiency and cost savings than that of considering inventory and transportation respectively.This paper studies the integrated inventory-transportation optimization problem systematically and synthetically based on fuzzy environment, with integration optimal decision made on inventory and transportation in the two-echelon supply chain. Firstly, the paper investigates the theoretical basis of the integrated optimization problem systematically, summarizes the research situation and brings forward the integrated inventory-transportation problem systematically based on fuzzy environment on the basis of analyzing deeply the integrated optimization problem based on stochastic environment. Secondly, based on fuzzy environment, the paper considers the two-echelon supply chain system consisted of one supplier and m retailers, assuming distributing a sort of goods, costs parameter(including inventory cost and order cost) and annual demand of supplier and retailers are mutually independent fuzzy variables. Goods of supplier and retailers is not out of stock, goods demand possesses periodicity, supplier places an order for goods to exterior supplier, the delivery cycle is constant, all retailers are mutually independent and in different location, transportation costs and inventory costs are mutually different. The paper regards inventory and transportation as whole and balances both the transportation and inventory to satisfy demand by the minimal total cost. Based on an expected value criterion, two fuzzy expected value models are constructed. Thirdly, for the sake of solving core question of model algorithm and determine algorithm searching extension, some properties of objective function such as convexity, continuity, extreme value of break point and upper bound of n and so on are analyzed deeply and proved. Finally, numerical results show the feasibility and validity of the two models.